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MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment


Dec 10, 2021
Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu

* 15 pages, code: https://github.com/MegviiRobot/MegBA 

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Trap of Feature Diversity in the Learning of MLPs


Dec 02, 2021
Dongrui Liu, Shaobo Wang, Jie Ren, Kangrui Wang, Sheng Yin, Quanshi Zhang


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Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models


Nov 30, 2021
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang


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Discovering and Explaining the Representation Bottleneck of DNNs


Nov 18, 2021
Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang


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A Unified Game-Theoretic Interpretation of Adversarial Robustness


Nov 08, 2021
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang

* the previous version is arXiv:2103.07364, but I mistakenly apply a new ID for the paper 

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ESOD:Edge-based Task Scheduling for Object Detection


Oct 20, 2021
Yihao Wang, Ling Gao, Jie Ren, Rui Cao, Hai Wang, Jie Zheng, Quanli Gao

* Accepted by The Ninth International Conference on Advanced Cloud and Big Data 

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Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks


Oct 05, 2021
Xin Zhang, Xiujun Shu, Bingwen Zhang, Jie Ren, Lizhou Zhou, Xin Chen

* Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August, 2020, Pages 2378 

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Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI


Jul 26, 2021
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang


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Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network


Jun 30, 2021
Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou


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A Game-Theoretic Taxonomy of Visual Concepts in DNNs


Jun 21, 2021
Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang

* 12 pages 

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A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection


Jun 16, 2021
Jie Ren, Stanislav Fort, Jeremiah Liu, Abhijit Guha Roy, Shreyas Padhy, Balaji Lakshminarayanan


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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning


Jun 07, 2021
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran


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Exploring the Limits of Out-of-Distribution Detection


Jun 06, 2021
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan

* S.F. and J.R. contributed equally 

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Learning Baseline Values for Shapley Values


May 22, 2021
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang


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Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning


Apr 19, 2021
Jie Ren, Yewen Li, Zihan Ding, Wei Pan, Hao Dong


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Learning to Remove: Towards Isotropic Pre-trained BERT Embedding


Apr 12, 2021
Yuxin Liang, Rui Cao, Jie Zheng, Jie Ren, Ling Gao


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Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning


Apr 11, 2021
Tong Chen, Hongzhi Yin, Jie Ren, Zi Huang, Xiangliang Zhang, Hao Wang

* Manuscript is under review 

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Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions


Apr 08, 2021
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zach Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Greg S. Corrado, Umesh Telang, Yun Liu, Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens

* Under Review, 19 Pages 

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Game-theoretic Understanding of Adversarially Learned Features


Mar 12, 2021
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang


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ZeRO-Offload: Democratizing Billion-Scale Model Training


Jan 18, 2021
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He


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A Unified Approach to Interpreting and Boosting Adversarial Transferability


Oct 08, 2020
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang


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Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks


Jul 10, 2020
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Liu, Jasper Snoek, Balaji Lakshminarayanan


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Interpreting and Disentangling Feature Components of Various Complexity from DNNs


Jun 29, 2020
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang


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SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders


Oct 02, 2019
Peter J. Liu, Yu-An Chung, Jie Ren

* first two authors contributed equally 

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